Senior Data Engineer — Onsite, Real-Time ETL & AI

Airwallex; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Airwallex, the AI-native financial operating system, is building the data foundations for its Customer Data Platform in Singapore. This in-office role will contribute to scalable ETL pipelines and reliable data foundations across data warehouses and modern cloud infrastructure.

You’ll develop data models supporting analytics, ML, and business intelligence, using star/snowflake/denormal designs, and apply AI best practices to practical problems while coordinating with globally distributed teams.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Mathematics, or related field.
• At least seven years designing and implementing scalable ETL pipelines (batch and streaming).
• Experience with streaming tech (Kafka or Flink).
• Strong SQL, data warehousing, and BI-oriented data modeling.
• Understanding of data schemas (star, snowflake, denormalised).
• Excellent analytical, problem-solving, and collaboration skills.
• Interest in applying AI to data engineering in practical ways.

Responsibilities

• Own scalable ETL pipelines across batch and real-time workflows.
• Build reliable data foundations across data warehouses and data platforms.
• Develop data models and products for analytics, ML, and BI.
• Apply data engineering and AI best practices to solve practical problems.
• Collaborate with globally distributed teams to deliver complex work.

Skills

Bachelor level degree

7+ years ETL design

Streaming technologies

SQL and data warehousing

Data modeling (star/snowflake/denormal

Analytical thinking

AI awareness/use of data engineering

Education

Bachelor’s degree in CS/IS/Math

Tools

Databricks

Airflow

Kafka

Flink

Job description

Airwallex, the AI-native financial operating system, is building the data foundations for its Customer Data Platform in Singapore. This in-office role will contribute to scalable ETL pipelines and reliable data foundations across data warehouses and modern cloud infrastructure.

You’ll develop data models supporting analytics, ML, and business intelligence, using star/snowflake/denormal designs, and apply AI best practices to practical problems while coordinating with globally distributed teams.